Run
23216

Run 23216

Task 23 (Supervised Classification) cmc Uploaded 24-06-2014 by Joaquin Vanschoren
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Flow

weka.MultiBoostAB_BFTree(1)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.BFTree(1)_Ctrue
weka.BFTree(1)_M2
weka.BFTree(1)_N5
weka.BFTree(1)_PPOSTPRUNED
weka.BFTree(1)_S1
weka.MultiBoostAB_BFTree(1)_C3
weka.MultiBoostAB_BFTree(1)_I160
weka.MultiBoostAB_BFTree(1)_P100
weka.MultiBoostAB_BFTree(1)_S1
weka.MultiBoostAB_BFTree(1)_Wweka.classifiers.trees.BFTree

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.6941
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5194
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2549
Cross-validation details (10-fold Crossvalidation)
KB relative information score
438.6818
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3284
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4308
Cross-validation details (10-fold Crossvalidation)
Number of instances
1473
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5181
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.5214
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.5392
Cross-validation details (10-fold Crossvalidation)
Recall
0.5214
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7623
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4641
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5082
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.095
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
910.7243[559.5895783704208977.9015556766286475.31735608978465905.19339878208931635.6194534804458]